Frontiers of Data and Computing ›› 2019, Vol. 1 ›› Issue (1): 82-93.

doi: 10.11871/jfdc.issn.2096.742X.2019.01.009

Special Issue: “数据与计算平台”专刊

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SKS: A Platform for Big Data Based Scientific Knowledge Graph

Yuanchun Zhou1,2,Qingling Chang1,Yi Du1   

  1. 1.Department of Big Data Technology and Application Development, Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-08-15 Online:2019-01-20 Published:2019-10-09

Abstract:

[Objective] The big data knowledge graph in the field of science and technology is dedicated to providing researchers with more accurate, comprehensive, deeper and broader search and analysis results, and thus providing a practical and valuable reference for disciplinary research. [Scope of the literature] The article focuses on the research of data-based scientific and technological evaluation methods at home and abroad, the interdisciplinary research based on knowledge graph, the key technical methods in the construction of knowledge graph and the application of knowledge graph based on domain knowledge. [Methods] This paper presents a large-data knowledge graph platform SKS in the field of science and technology. Based on the overall architecture of the SKS platform, we expound the key technologies and platform tools for constructing knowledge graph in the field of science and technology, and gives relevant key technologies and applications in different fields. [Results] The SKS platform and application provide a precise, multi-dimensional and interrelated intelligent retrieval service for researchers while constructing a resource knowledge management system for related fields. [Limitations] The big data knowledge graph in the field of science and technology is constantly developing. The data quality (the error caused by the data fusion and the quality of source data) affects the application effect of the platform to a certain extent. In the future, we hope to carry out more in data disambiguation. [Conclusions] The big data knowledge graph in the field of science and technology, with its strong semantic processing ability and relationship exploration ability, can organize massive data of personnel, institutions, achievements, events, etc. in the field of science and technology in a better way, which provides auxiliary functions for technology evaluation. The application effects in specific projects are recognized by corresponding domain experts.

Key words: Knowledge graph, Big data, Data collection, Convergence and merge, Linkage, Visualization